DBMS > GigaSpaces vs. Microsoft Access vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics vs. MongoDB

System Properties Comparison GigaSpaces vs. Microsoft Access vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics vs. MongoDB

Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Search-as-a-service for web and mobile app development

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Graph DBMS
Search engine

Vector DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Website

www.gigaspaces.com

www.microsoft.com/en-us/microsoft-365/access

azure.microsoft.com/en-us/services/search

azure.microsoft.com/services/synapse-analytics

www.mongodb.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

developer.microsoft.com/en-us/access

learn.microsoft.com/en-us/azure/search

docs.microsoft.com/azure/synapse-analytics

www.mongodb.com/docs/manual

Developer

Gigaspaces Technologies

Microsoft

MongoDB, Inc

Initial release

2000

1992

2015

2016

2009

Current release

15.5, September 2020

1902 (16.0.11328.20222), March 2019

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Bundled with Microsoft Office

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java, C++, .Net

C++

Server operating systems

Linux
macOS
Solaris
Windows

Windows

Not a real database server, but making use of DLLs

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

but not compliant to any SQL standard

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

ADO.NET
JDBC
ODBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

.Net
C++
Java
Python
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C#
Java
JavaScript
Python

C#
Java
PHP

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

Transact SQL

JavaScript

Triggers

yes, event driven architecture

yes

since Access 2010 using the ACE-engine

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

yes

Implicit feature of the cloud service

yes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

but no files for transaction logging

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

optional, enabled by default

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Role-based access control

a simple user-level security was built in till version Access 2003

yes

using Azure authentication

yes

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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